DAX / Power BI - Data Analysis Techniques Part 2
Expand your Power BI skills! Learn 10 advanced DAX & data analysis techniques. A continuation of our popular course.
Course Content
DAX / Power BI - Data Analysis Techniques Part 2 is an all-levels Udemy course taught by Randy Minder. It runs 4h 17m, is taught in English, and includes a certificate of completion. Learners rate it 4.7 out of 5 from 6 reviews, with 237 students enrolled. It is a paid course, first published July 2021.
Unlock Powerful Data Insights with DAX and Power BI: A Comprehensive Data Analysis Course
Dive deep into the world of data analysis with this two-part series focused on DAX and Power BI. Master essential techniques to transform raw data into actionable intelligence. This course is designed to elevate your data analysis skills and prepare you for the DA-100 exam.
Part 1: Foundations of Data Analysis with DAX & Power BI (4+ hours)
This extensive first part covers a broad spectrum of compelling data analysis techniques, including:
- Anomaly Detection: Identify unusual patterns and outliers in your data.
- Key Influencer Analysis: Discover the factors driving significant changes.
- Forecasting Analysis: Predict future trends and outcomes.
- Decomposition Tree Analysis: Understand the components contributing to data fluctuations.
- Q&A Analysis: Extract insights through natural language queries.
- Plus, at least 10 more valuable data analysis techniques!
Reinforce your learning with practical exercises after each technique.
Part 2: Advanced Data Analysis Techniques with DAX & Power BI
Continue your journey to become a proficient data analyst with Part 2, covering a wide range of advanced techniques:
- Cohort Analysis: Analyze the behavior of groups over time.
- Cross-selling Analysis: Identify opportunities to increase sales.
- Pareto Analysis: Focus on the vital few factors driving results.
- Simple Clustering Analysis: Group similar data points together.
- Ranking Analysis: Understand the relative importance of different elements.
- Attrition Analysis: Identify and address customer churn.
- R Integration: Leverage the power of R for advanced statistical analysis.
- Percentile Analysis: Understand data distribution and identify outliers.
- Scenario / Sensitivity Analysis: Evaluate the impact of different variables.
This course provides hands-on practice to solidify your understanding of each data analysis technique.
Important Note: There are no plans for a Part 3. We are open to suggestions! If you have specific data analysis areas you'd like us to cover, please let us know, and we'll consider incorporating them into Part 1 or Part 2. This course is an excellent resource for anyone seeking to improve their Power BI skills and DAX proficiency.
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